| Title | Queue discharging characteristics in mixed traffic considering the stopping queue patterns |
| Year | 2018 |
| Degree | Master |
| School | Department of Transportation and Logistics Management College of Management National Chiao Tung University |
| Author | Wei Hao Huang |
| Summary | The mixed traffic condition is common in most of the developing countries. In Taiwan, the large ratio of scooters in the mixed traffic increase s the complexity of interaction s between vehicles. To understand the capacity of signali s ed intersections, the discharge characteristics under the mixed traffic condition is critical. The less bias on the estimation of discharge time can improve the estimation of discharge flow rate of intersection s . The aim of this study is to understand the discharge behaviour of vehicles under the mixed flow traffic condition and formulate a model to estimate the di scharge time. Past research discovered the relationship between the discharge time and the affecting factors , such as n umbers of the vehicles, length of the queue, geometry design and layout , and the interaction s between vehicles. However, there were limited studies that investigated the effect of order and arrangement of vehicles in a queue to the discharge process . In Taiwan’s Highway Capacity Manual, it is assumed that scooters concentrate at the scooter waiting zone and their discharge do not affect the vehicles behind. H owever, in observations, scooters and other vehicles may mix up in the queue . This study proposed a new factor, Queue Pattern Entropy (QPE), which can describe the vehicle stopping sequence and queue pattern formed by different vehicle compositions . Microscopic vehicle trajectory data collected from Unmanned Aerial Vehicle UAV is used in this study to gain insight s in to the interaction s between vehicles . The dataset allowed us to observe traffic characteristics such as lateral movement discharge order, and discharge times of the mixed traffic flow. Furthermore, a regression analysis is proposed to construct a discharge time estimation model under mixed traffic condition. Linear and non linear structure has been calibrated and compared to the model without QPE . Both form s of the model show s that the QPE is beneficial and superior to the base model Compared with previous model s in the literature , our model with QPE can effectivel y describe the queue pattern and attain less bias on the discharge time estimation |
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